Tissue resolved, gene structure refined equine transcriptome

T. A. Mansour, E. Y. Scott, Carrie J Finno, Rebecca Bellone, M. J. Mienaltowski, Cecilia Penedo, P. J. Ross, S. J. Valberg, J. D. Murray, Charles Brown

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Background: Transcriptome interpretation relies on a good-quality reference transcriptome for accurate quantification of gene expression as well as functional analysis of genetic variants. The current annotation of the horse genome lacks the specificity and sensitivity necessary to assess gene expression especially at the isoform level, and suffers from insufficient annotation of untranslated regions (UTR) usage. We built an annotation pipeline for horse and used it to integrate 1.9 billion reads from multiple RNA-seq data sets into a new refined transcriptome. Results: This equine transcriptome integrates eight different tissues from 59 individuals and improves gene structure and isoform resolution, while providing considerable tissue-specific information. We utilized four levels of transcript filtration in our pipeline, aimed at producing several transcriptome versions that are suitable for different downstream analyses. Our most refined transcriptome includes 36,876 genes and 76,125 isoforms, with 6474 candidate transcriptional loci novel to the equine transcriptome. Conclusions: We have employed a variety of descriptive statistics and figures that demonstrate the quality and content of the transcriptome. The equine transcriptomes that are provided by this pipeline show the best tissue-specific resolution of any equine transcriptome to date and are flexible for several downstream analyses. We encourage the integration of further equine transcriptomes with our annotation pipeline to continue and improve the equine transcriptome.

Original languageEnglish (US)
Article number103
JournalBMC Genomics
Issue number1
StatePublished - Jan 20 2017


  • Equine transcriptome
  • RNA-seq
  • Tissue-specificity

ASJC Scopus subject areas

  • Biotechnology
  • Genetics


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